• Steel and Composite Structures
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• v.32 no.6
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• pp.701-715
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• 2019

Using first-order shear deformation theory (FSDT), a semi-analytical solution is employed to analyze creep damage and remaining life assessment of 304L austenitic stainless steel thick (304L ASS) cylindrical pressure vessels with variable thickness subjected to the temperature gradient and internal non-uniform pressure. Damages are obtained in thick cylinder using Robinson's linear life fraction damage rule, and time to rupture and remaining life assessment is determined by Larson-Miller Parameter (LMP). The thermo-elastic creep response of the material is described by Norton's law. The novelty of the present work is that it seeks to investigate creep damage and life assessment of the vessels with variable thickness made of 304L ASS using LMP based on first-order shear deformation theory. A numerical solution using finite element method (FEM) is also presented and good agreement is found. It is shown that temperature gradient and non-uniform pressure have significant influences on the creep damages and remaining life of the vessel.

• The Transactions of the Korea Information Processing Society
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• v.13 no.5
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• pp.217-220
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• 2024

Predicting earthquake occurrences accurately is challenging, and preparing all buildings with seismic design for such random events is a difficult task. Analyzing building features to predict potential damage and reinforcing vulnerabilities based on this analysis can minimize damages even in buildings without seismic design. Therefore, research analyzing the efficiency of building damage prediction models is essential. In this paper, we compare the accuracy of earthquake damage prediction models using machine learning classification algorithms, including Random Forest, Extreme Gradient Boosting, LightGBM, and CatBoost, utilizing data from buildings damaged during the 2015 Nepal earthquake.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.10a
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• pp.313-318
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• 1998

Generally, the concrete constructed during cold weather has the frozen damage which cause the fatal damage so that heat curing and sheet curing was performed to prevent the early freezing of concrete. However, partial refrigeration caused by thermal gradient has many troubles so that the construction hasn`t been done as possible. This paper presents the development of strenth properties and optimal mix design against frozen damage under the cold weather, 1$0^{\circ}C$ below the zero.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.11a
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• pp.528-535
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• 2011

In the present, the formation of shear band under a simple shear deformation is investigated using a rate-independent elastic-plastic constitutive relations. Moreover, the strain gradient terms are incorporated to obtain a non-local plastic constitutive relation, which in turn represented using combined two-back stress hardening model. Then, the continuum damage model is also included to the proposed model. The post-localization behavior are studied by introducing a small imperfection in a work piece. The strain gradient affects the shear localization significantly such that the intensity of shear band decreases as the strain gradient coefficient increases when the J2 flow theory is employed.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.395-418
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• 2024

The epicentral region of earthquakes is typically where liquefaction-related damage takes place. To determine the maximum distance, such as maximum epicentral distance (R_e), maximum fault distance (R_f), or maximum hypocentral distance (R_h), at which an earthquake can inflict damage, given its magnitude, this study, using a recently updated global liquefaction database, multiple ML models are built to predict the limiting distances (R_e, R_f, or R_h) required for an earthquake of a given magnitude to cause damage. Four machine learning models LSTM (Long Short-Term Memory), BiLSTM (Bidirectional Long Short-Term Memory), CNN (Convolutional Neural Network), and XGB (Extreme Gradient Boosting) are developed using the Python programming language. All four proposed ML models performed better than empirical models for limiting distance assessment. Among these models, the XGB model outperformed all the models. In order to determine how well the suggested models can predict limiting distances, a number of statistical parameters have been studied. To compare the accuracy of the proposed models, rank analysis, error matrix, and Taylor diagram have been developed. The ML models proposed in this paper are more robust than other current models and may be used to assess the minimal energy of a liquefaction disaster caused by an earthquake or to estimate the maximum distance of a liquefied site provided an earthquake in rapid disaster mapping.

• Asia pacific journal of information systems
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• v.34 no.2
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• pp.565-584
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• 2024

More than 1 million automobile insurance repairs occur per year globally, and the related repair costs add up to astronomical amounts. Insurance companies and repair shops are spending a great deal of money on manpower every year to claim reasonable insurance repair costs. For this reason, promptly predicting insurance claims for vehicles in accidents can help reduce social costs related to auto insurance. Several recent studies have been conducted in auto insurance repair prediction using variables such as photos of vehicle damage. We propose a new model that reflects auto insurance repair characteristics to predict auto insurance repair claims through an association rule method that combines gradient descent and location information. This method searches for the appropriate number of rules by applying the gradient descent method to results generated by association rules and eventually extracting main rules with a distance filter that reflects automobile part location information to find items suitable for insurance repair claims. According to our results, predictive performance could be improved by applying the rule set extracted by the proposed method. Therefore, a model combining the gradient descent method and a location-based association rule method is suitable for predicting auto insurance repair claims.

• Journal of Environmental Science International
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• v.23 no.3
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• pp.483-492
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• 2014

DNA damage such as genotoxicity was identified with comet assay, which blood cell of a marine parrot fish (Oplegnathus fasciatus) was exposed to an acidified seawater, lowered pH gradient making of $CO_2$ gas. The gradient of pH were 8.22, 8.03, 7.81, 7.55 with control as HBSS solution with pH 7.4. DNA tail moment of fish blood cell was $0.548{\pm}0.071$ exposed seawater of pH 8.22 condition, on the other hand, DNA tail moment $1.601{\pm}0.197$ exposed acidified seawater of pH 7.55 lowest condition. The approximate difference with level of DNA damage was 2.9 times between highest and lowest of pH. DNA damage with decreasing pH was significantly increased with DNA tail moment on blood cell of marine fish (ANOVA, p < 0.001). Ocean acidification, especially inducing the leakage of sequestered $CO_2$ in geological structure is a consequence from the burning of fossil fuels, and long term effects on marine habitats and organisms are not fully investigated. The physiological effects on adult fish species are even less known. This result shown that the potential of dissolved $CO_2$ in seawater was revealed to induce the toxic effect on genotoxicity such as DNA breakage.

• Structural Engineering and Mechanics
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• v.53 no.2
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• pp.249-260
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• 2015

Damage detection based on a reference set of measured data usually has the problem of different environmental temperature in the two sets of measurements, and the effect of temperature difference is usually ignored in the subsequent model updating. This paper attempts to identify the structural damage including the temperature difference with artificial measurement noise. Both local damages and the temperature difference are identified in a gradient-based model updating method based on dynamic response sensitivity. The sensitivities of dynamic response with respect to the system parameters and temperature difference are calculated by direct integration method. The measured dynamic responses of the structure from two different states are used directly to identify the structural local damages and the temperature difference. A single degree-of-freedom mass-spring system and a planar truss structure are studied to illustrate the effectiveness of the proposed method.

• Smart Structures and Systems
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• v.8 no.2
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• pp.157-172
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• 2011

A new method for both local damage(s) identification and input excitation force identification of beam structures is presented using the dynamic response sensitivity-based finite element model updating method. The state-space approach is used to calculate both the structural dynamic responses and the responses sensitivities with respect to structural physical parameters such as elemental flexural rigidity and with respect to the force parameters as well. The sensitivities of displacement and acceleration responses with respect to structural physical parameters are calculated in time domain and compared to those by using Newmark method in the forward analysis. In the inverse analysis, both the input excitation force and the local damage are identified from only several acceleration measurements. Local damages and the input excitation force are identified in a gradient-based model updating method based on dynamic response sensitivity. Both computation simulations and the laboratory work illustrate the effectiveness and robustness of the proposed method.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.545-559
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• 2010

This paper presents the results of a pilot study and verification of a concept of a novel methodology for damage detection and assessment of water distribution system. The unique feature of the proposed noninvasive methodology is the use of accelerometers installed on the pipe surface, instead of pressure sensors that are traditionally installed invasively. Experimental observations show that a sharp change in pressure is always accompanied by a sharp change of pipe surface acceleration at the corresponding locations along the pipe length. Therefore, water pressure-monitoring can be transformed into acceleration-monitoring of the pipe surface. The latter is a significantly more economical alternative due to the use of less expensive sensors such as MEMS (Micro-Electro-Mechanical Systems) or other acceleration sensors. In this scenario, monitoring is made for Maximum Pipe Acceleration Gradient (MPAG) rather than Maximum Water Head Gradient (MWHG). This paper presents the results of a small-scale laboratory experiment that serves as the proof of concept of the proposed technology. The ultimate goal of this study is to improve upon the existing SCADA (Supervisory Control And Data Acquisition) by integrating the proposed non-invasive monitoring techniques to ultimately develop the next generation SCADA system for water distribution systems.